The goal of the proposed research is to develop a wearable "early warning" device attached to an implantable microelectrode array that will give otherwise untreatable epilepsy patients enough time to take a medicine or prepare for the seizure (e.g. get out of the pool, pull the car over to side of the road or get off a ladder or stairs). The device would use detector software based on advanced machine learning technology to detect an impending seizure. The learning system would be trained with data from the implanted

To develop a combination of hardware and software to automatically detect High Frequency Oscillations (HFOs) in real-time and in a clinical setting

Description:
Online High Frequency Oscillation Detection

High frequency oscillations (HFOs), or brief bursts in the high gamma band (80-500 Hz), have been studied as potential biomarkers of epileptic activity. Since the early 1990's, it has been recognized that increased high gamma power is present within the epileptogenic region at seizure onset in adults (Allen, Fish et al. 1992; Alarcon, Binnie et al. 1995) and children (Fisher, Webber et al. 1992; Traub, Whittington et al. 2001). Interictal fast ripples (Figure 1) have been detected almost exclusively in epileptogenic regions (Staba, Wilson et al. 2002; Jacobs, Levan et al.